AIMC Topic: Phenotype
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Plasma infrared fingerprinting with machine learning enables single-measurement multi-phenotype health screening.
Cell reports. Medicine
Jun 28, 2024
Infrared spectroscopy is a powerful technique for probing the molecular profiles of complex biofluids, offering a promising avenue for high-throughput in vitro diagnostics. While several studies showcased its potential in detecting health conditions,...
Exploring the diagnostic performance of machine learning in prediction of metabolic phenotypes focusing on thyroid function.
PloS one
Jun 28, 2024
In this study, we employed various machine learning models to predict metabolic phenotypes, focusing on thyroid function, using a dataset from the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2012. Our analysis utilized labo...
Individual characteristics outperform resting-state fMRI for the prediction of behavioral phenotypes.
Communications biology
Jun 26, 2024
In this study, we aimed to compare imaging-based features of brain function, measured by resting-state fMRI (rsfMRI), with individual characteristics such as age, gender, and total intracranial volume to predict behavioral measures. We developed a ma...
Deep representation learning of chemical-induced transcriptional profile for phenotype-based drug discovery.
Nature communications
Jun 25, 2024
Artificial intelligence transforms drug discovery, with phenotype-based approaches emerging as a promising alternative to target-based methods, overcoming limitations like lack of well-defined targets. While chemical-induced transcriptional profiles ...
Editorial: Artificial intelligence in predicting, determining and controlling cell phenotype or tissue function in inflammatory diseases.
Frontiers in immunology
Jun 18, 2024
Deep cell phenotyping and spatial analysis of multiplexed imaging with TRACERx-PHLEX.
Nature communications
Jun 15, 2024
The growing scale and dimensionality of multiplexed imaging require reproducible and comprehensive yet user-friendly computational pipelines. TRACERx-PHLEX performs deep learning-based cell segmentation (deep-imcyto), automated cell-type annotation (...
Artificial intelligence approaches for phenotyping heart failure in U.S. Veterans Health Administration electronic health record.
ESC heart failure
Jun 14, 2024
AIMS: Heart failure (HF) is a clinical syndrome with no definitive diagnostic tests. HF registries are often based on manual reviews of medical records of hospitalized HF patients identified using International Classification of Diseases (ICD) codes....
Dual-extraction modeling: A multi-modal deep-learning architecture for phenotypic prediction and functional gene mining of complex traits.
Plant communications
Jun 13, 2024
Despite considerable advances in extracting crucial insights from bio-omics data to unravel the intricate mechanisms underlying complex traits, the absence of a universal multi-modal computational tool with robust interpretability for accurate phenot...
Mapping the landscape of histomorphological cancer phenotypes using self-supervised learning on unannotated pathology slides.
Nature communications
Jun 11, 2024
Cancer diagnosis and management depend upon the extraction of complex information from microscopy images by pathologists, which requires time-consuming expert interpretation prone to human bias. Supervised deep learning approaches have proven powerfu...
Integrating genomics, phenomics, and deep learning improves the predictive ability for Fusarium head blight-related traits in winter wheat.
The plant genome
Jun 9, 2024
Fusarium head blight (FHB) remains one of the most destructive diseases of wheat (Triticum aestivum L.), causing considerable losses in yield and end-use quality. Phenotyping of FHB resistance traits, Fusarium-damaged kernels (FDK), and deoxynivaleno...
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